Reduced order modeling and model order reduction for continuum manipulators: an overview

Front Robot AI. 2023 Sep 15:10:1094114. doi: 10.3389/frobt.2023.1094114. eCollection 2023.

Abstract

Soft robot's natural dynamics calls for the development of tailored modeling techniques for control. However, the high-dimensional configuration space of the geometrically exact modeling approaches for soft robots, i.e., Cosserat rod and Finite Element Methods (FEM), has been identified as a key obstacle in controller design. To address this challenge, Reduced Order Modeling (ROM), i.e., the approximation of the full-order models, and Model Order Reduction (MOR), i.e., reducing the state space dimension of a high fidelity FEM-based model, are enjoying extensive research. Although both techniques serve a similar purpose and their terms have been used interchangeably in the literature, they are different in their assumptions and implementation. This review paper provides the first in-depth survey of ROM and MOR techniques in the continuum and soft robotics landscape to aid Soft Robotics researchers in selecting computationally efficient models for their specific tasks.

Keywords: continuum robot; dynamics; model order reduction (MOR); reduced order model (ROM); soft robot.

Publication types

  • Review